CHICKPEA (CICER ARIETINUM L.) GENOTYPES EVALUATION FOR HIGH YIELD THROUGH MULTIVARIATE ANALYSIS

Abstract

Assessment of crop accessions through yield components is the most popular way for selecting welladapted and stable genotypes for certain growing conditions. Chickpea (Cicer arietinum L.) is an important food legume crop in Uzbekistan. The 71 chickpea genotypes received an evaluation for morphological and yield traits through principal component, cluster, and biplot analyses. Principal component analysis (PCA) estimated chickpea variables into two main components accounting for 76.32% of the total variation. In chickpea genotypes, the traits viz., plant height, number of pods per plant, pods weight per plant, number of seeds per plant, seed weight, and seed yield showed a positive relationship with the first component (PC-I). Seed yield and the number of branches showed a positive correlation with the second component (PC-II). Biplot analysis indicated a positive association of seed yield (SY) with the number of branches (Br), number of pods per plant (NPP), number of seeds per plant (SPP), seed weight (SW), pod weight (PW), yet a negative association with plant height (PH). The 36 winter and 35 spring chickpea genotypes underwent analysis, then clustered based on various yield traits. The chickpea genotypes grouped into six clusters used the cluster analysis. Genotypes in cluster I and cluster VI showed the highest grain yield whereas cluster II and cluster III included the taller genotypes found suitable for mechanical harvesting. These findings can serve beneficial in chickpea hybridization for yield improvement in future breeding programs.